Simulations in large tridimensional Discrete Fracture Networks (DFN): I. Geometric modeling and mesh generation

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Simulations in large tridimensional Discrete Fracture Networks (DFN): I. Geometric modeling and mesh

generation

Patrick Laug, Géraldine Pichot

To cite this version:

Patrick Laug, Géraldine Pichot. Simulations in large tridimensional Discrete Fracture Networks

(DFN): I. Geometric modeling and mesh generation. MASCOT 2018 - 15th IMACS/ISGG meet-

ing on applied scientific computing and tools, Oct 2018, Rome, Italy. pp.1-2. �hal-01896881�

Simulations in large tridimensional Discrete Fracture Networks (DFN):

I. Geometric modeling and mesh generation

Patrick Laug ¹ , G´ eraldine Pichot ²

1

Inria Saclay ˆIle-de-France, France

2

Inria Paris, France

Fractures in the Earth’s subsurface have a strong impact in many physical and chemical phenomena, as their properties (in particular their permeabil- ities) are very different from those of the surrounding rocks. They play a major role in diverse fields of applications such as groundwater extraction, oil and gas exploitation, geothermal energy production, CO2 sequestration, etc. In this presentation, we focus on the well-known Discrete Fracture Net- work (DFN) models and on efficient techniques to mesh them. The generated meshes are subsequently used to carry out numerical simulations

.

In the DFN models [1, 2, 3, 4], fractures are represented by ellipses that are randomly generated in the tridimensional space, following experimental statistics. To make this model suitable for classical surface and volume mesh- ers [5, 6], it is necessary to add some information, which is accomplished in several steps: computation of the intersections between fractures, selection of fractures using a graph structure, and construction of a conforming set of edges that can be used as input for a mesh generator. All these steps present special difficulties if there are large numbers of fractures with dis- tances, lengths and angles spanning over several orders of magnitude. Com- putational times are also critical, and only linear time algorithms can be accepted. In this talk, a methodology for modeling and meshing DFNs will be presented, and recent meshes up to hundreds of thousands of fractures will be shown.

∗

See Pichot et al. MASCOT 2018 abstract, Simulations in large tridimensional Discrete Fracture Networks (DFN): II. Flow simulations.

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References

[1] P. Laug, G. Pichot and J.R. de Dreuzy. Realistic geometric modeling of fracture networks. ADMOS (2017).

[2] J.R. de Dreuzy, G. Pichot, B. Poirriez and J. Erhel. Synthetic benchmark for modeling flow in 3D fractured media. Computers & Geosciences 50, 59–71 (2013).

[3] P. Davy, R. Le Goc, C. Darcel, O. Bour, J.R. de Dreuzy and R. Munier.

A likely universal model of fracture scaling and its consequence for crustal hydromechanics. Journal of Geophysical Research: Solid Earth, 115 (B10) (2010).

[4] P. Davy, R. Le Goc and C. Darcel. A model of fracture nucleation, growth and arrest, and consequences for fracture density and scaling. Journal of Geophys- ical Research: Solid Earth, 118 (4), 1393–1407 (2013).

[5] H. Borouchaki, P. Laug and P.L. George. Parametric surface meshing using a combined advancing-front – generalized-Delaunay approach, Int. Journal for Numerical Methods in Engineering, 49 (1–2), pp. 233–259 (2000).

[6] H. Borouchaki and P.L. George. Meshing, Geometric Modeling and Numerical Simulation 1. John Wiley & Sons, 384 pages (2017).

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